.png){kind=icon}
返回
Using kNN model for automatic text categorization
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-005-0503-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
An investigation is conducted on two well-known similarity-based learning approaches to text categorization: the k-nearest neighbors (kNN) classifier and the Rocchio classifier. After identifying the weakness and strength of each technique, a new classifier called the kNN model-based classifier (kNN Model) is proposed. It combines the strength of both kNN and Rocchio. A text categorization prototype, which implements kNN Model along with kNN and Rocchio, is described. An experimental evaluation of different methods is carried out on two common document corpora: the 20-newsgroup collection and the ModApte version of the Reuters-21578 collection of news stories. The experimental results show that the proposed kNN model-based method outperforms the kNN and Rocchio classifiers, and is therefore a good alternative for kNN and Rocchio in some application areas.
Keyword:
kNN model
kNN
Rocchio
text categorization
performance
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
机构
暂无机构信息
引用论文
分享收藏
Preparation of water-dispersible TiO2 nanoparticles from titanium tetrachloride using urea hydrogen peroxide as an oxygen donor.png)
CrystEngComm
OAAI
CrystEngCommIF0
OAAI分享收藏Physiology and tonotopic organization of auditory receptors in the cricketGryllus bimaculatus DeGeer
PREAI
分享收藏Researchers' roles in knowledge co-production: experience from sustainability research in Kenya, Switzerland, Bolivia and Nepal研究人员在知识联合生产中的作用: 肯尼亚，瑞士，玻利维亚和尼泊尔的可持续性研究经验OAAI
OAAI分享收藏
查看更多内容